Integrating monitor alarms with laboratory test results to enhance patient deterioration prediction

AbstractPatient monitors in modern hospitals have become ubiquitous but they generate an excessive number of false alarms causing alarm fatigue. Our previous work showed that combinations of frequently co-occurring monitor alarms, called SuperAlarm patterns, were capable of predicting in-hospital code blue events at a lower alarm frequency. In the present study, we extend the conceptual domain of a SuperAlarm to incorporate laboratory test results along with monitor alarms so as to build an integrated data set to mine SuperAlarm patterns. We propose two approaches to integrate monitor alarms with laboratory test results and use a maximal frequent itemsets mining algorithm to find SuperAlarm patterns. Under an acceptable false positive rate FPRmax, optimal parameters including the minimum support threshold and the length of time window for the algorithm to find the combinations of monitor alarms and laboratory test results are determined based on a 10-fold cross-validation set. SuperAlarm candidates are generated under these optimal parameters. The final SuperAlarm patterns are obtained by further removing the candidates with false positive rate>FPRmax. The performance of SuperAlarm patterns are assessed using an independent test data set. First, we calculate the sensitivity with respect to prediction window and the sensitivity with respect to lead time. Second, we calculate the false SuperAlarm ratio (ratio of the hourly number of SuperAlarm triggers for control patients to that of the monitor alarms, or that of regular monitor alarms plus laboratory test results if the SuperAlarm patterns contain laboratory test results) and the work-up to detection ratio, WDR (ratio of the number of patients triggering any SuperAlarm patterns to that of code blue patients triggering any SuperAlarm patterns). The experiment results demonstrate that when varying FPRmax between 0.02 and 0.15, the SuperAlarm patterns composed of monitor alarms along with the last two laboratory test results are triggered at least once for [56.7–93.3%] of code blue patients within an 1-h prediction window before code blue events and for [43.3–90.0%] of code blue patients at least 1-h ahead of code blue events. However, the hourly number of these SuperAlarm patterns occurring in control patients is only [2.0–14.8%] of that of regular monitor alarms with WDR varying between 2.1 and 6.5 in a 12-h window. For a given FPRmax threshold, the SuperAlarm set generated from the integrated data set has higher sensitivity and lower WDR than the SuperAlarm set generated from the regular monitor alarm data set. In addition, the McNemar’s test also shows that the performance of the SuperAlarm set from the integrated data set is significantly different from that of the SuperAlarm set from the regular monitor alarm data set. We therefore conclude that the SuperAlarm patterns generated from the integrated data set are better at predicting code blue events

Paths to improving postpartum care among Australian Aboriginal and Torres Strait Islander women after gestational diabetes

Background: Indigenous women in far north Queensland are less likely than non-Indigenous women to present for post-partum screening after gestational diabetes mellitus (GDM) despite a fourfold increased risk of type 2 diabetes within eight years of the pregnancy. Aim: To understand barriers and enablers to post-natal follow-up. Methods: We conducted interviews with Indigenous women with previous GDM, focus groups with Indigenous healthworkers and workshops with other health professionals. Data collection included brainstorming, visualisation, sorting and prioritising activities. Data was analysed thematically using the Theoretical Domains Framework. Barriers are presented under the headings of 'capability', 'motivation' and 'opportunity'. Enabling strategies are presented under 'intervention' and 'policy' headings. Results: Participants generated twenty-eight enabling environmental, educational and incentive interventions, and service provision, communication, guideline, persuasive and fiscal policies to address barriers to screening and improve postpartum support for women. The highest priorities included providing holistic social support, culturally appropriate resources, improving Indigenous workforce involvement and establishing structured follow-up systems. Conclusions: Understanding Indigenous women's perspectives, developing strategies with healthworkers, and action planning with other health professionals can generate context-relevant feasible strategies to improve postpartum care after GDM. However, we need to better understand how to effectively support Indigenous women and communities during the postpartum period

Paths to improving postpartum care among Australian Aboriginal and Torres Strait Islander women after gestational diabetes

Background: Indigenous women in far north Queensland are less likely than non-Indigenous women to present for post-partum screening after gestational diabetes mellitus (GDM) despite a fourfold increased risk of type 2 diabetes within eight years of the pregnancy. Aim: To understand barriers and enablers to post-natal follow-up. Methods: We conducted interviews with Indigenous women with previous GDM, focus groups with Indigenous healthworkers and workshops with other health professionals. Data collection included brainstorming, visualisation, sorting and prioritising activities. Data was analysed thematically using the Theoretical Domains Framework. Barriers are presented under the headings of 'capability', 'motivation' and 'opportunity'. Enabling strategies are presented under 'intervention' and 'policy' headings. Results: Participants generated twenty-eight enabling environmental, educational and incentive interventions, and service provision, communication, guideline, persuasive and fiscal policies to address barriers to screening and improve postpartum support for women. The highest priorities included providing holistic social support, culturally appropriate resources, improving Indigenous workforce involvement and establishing structured follow-up systems. Conclusions: Understanding Indigenous women's perspectives, developing strategies with healthworkers, and action planning with other health professionals can generate context-relevant feasible strategies to improve postpartum care after GDM. However, we need to better understand how to effectively support Indigenous women and communities during the postpartum period

Absence of Chordin-like 1 Aids Motor Recovery in a Mouse Model of Stroke

Chordin-like 1 (Chrdl1) is an astrocyte-secreted protein that regulates synaptic maturation, and limits plasticity via GluA2-containing AMPA receptors (AMPARs). It was demonstrated that Chrdl1 expression is very heterogeneous throughout the brain, and it is enriched in astrocytes in cortical layers 2/3, with peak expression in the visual cortex at postnatal day 14. In response to ischemic stroke, Chrdl1 is upregulated during the acute and sub-acute phases in the peri-infarct region, potentially hindering recovery after stroke. Here, we used photothrombosis to model ischemic stroke in the motor cortex of adult male and female mice. In this study, we demonstrate that elimination of Chrdl1 in a global knock-out mouse reduces apoptotic cell death at early post-stroke stages and prevents ischemia-driven synaptic loss of AMPA receptors at later time points, all contributing to faster motor recovery. This suggests that synapse-regulating astrocyte-secreted proteins such as Chrdl1 have therapeutic potential to aid functional recovery after an ischemic injury

Inflammation and infection in plasma cell disorders: how pathogens shape the fate of patients

The role of infection and chronic inflammation in plasma cell disorders (PCD) has been well-described. Despite not being a diagnostic criterion, infection is a common complication of most PCD and represents a significant cause of morbidity and mortality in this population. As immune-based therapeutic agents are being increasingly used in multiple myeloma, it is important to recognize their impact on the epidemiology of infections and to identify preventive measures to improve outcomes. This review outlines the multiple factors attributed to the high infectious risk in PCD (e.g. the underlying disease status, patient age and comorbidities, and myeloma-directed treatment), with the aim of highlighting future prophylactic and preventive strategies that could be implemented in the clinic. Beyond this, infection and pathogens as an entity are believed to also influence disease biology from initiation to response to treatment and progression through a complex interplay involving pathogen exposure, chronic inflammation, and immune response. This review will outline both the direct and indirect role played by oncogenic pathogens in PCD, highlight the requirement for large-scale studies to decipher the precise implication of the microbiome and direct pathogens in the natural history of myeloma and its precursor disease states, and understand how, in turn, pathogens shape plasma cell biology

Insights into high-risk multiple myeloma from an analysis of the role of PHF19 in cancer

Despite improvements in outcome, 15-25% of newly diagnosed multiple myeloma (MM) patients have treatment resistant high-risk (HR) disease with a poor survival. The lack of a genetic basis for HR has focused attention on the role played by epigenetic changes. Aberrant expression and somatic mutations affecting genes involved in the regulation of tri-methylation of the lysine (K) 27 on histone 3 H3 (H3K27me3) are common in cancer. H3K27me3 is catalyzed by EZH2, the catalytic subunit of the Polycomb Repressive Complex 2 (PRC2). The deregulation of H3K27me3 has been shown to be involved in oncogenic transformation and tumor progression in a variety of hematological malignancies including MM. Recently we have shown that aberrant overexpression of the PRC2 subunit PHD Finger Protein 19 (PHF19) is the most significant overall contributor to HR status further focusing attention on the role played by epigenetic change in MM. By modulating both the PRC2/EZH2 catalytic activity and recruitment, PHF19 regulates the expression of key genes involved in cell growth and differentiation. Here we review the expression, regulation and function of PHF19 both in normal and the pathological contexts of solid cancers and MM. We present evidence that strongly implicates PHF19 in the regulation of genes important in cell cycle and the genetic stability of MM cells making it highly relevant to HR MM behavior. A detailed understanding of the normal and pathological functions of PHF19 will allow us to design therapeutic strategies able to target aggressive subsets of MM

The spectrum and clinical impact of epigenetic modifier mutations in myeloma

Epigenetic dysregulation is known to be an important contributor to myeloma pathogenesis but, unlike in other B cell malignancies, the full spectrum of somatic mutations in epigenetic modifiers has not been previously reported. We sought to address this using results from whole-exome sequencing in the context of a large prospective clinical trial of newly diagnosed patients and targeted sequencing in a cohort of previously treated patients for comparison.Whole-exome sequencing analysis of 463 presenting myeloma cases entered in the UK NCRI Myeloma XI study and targeted sequencing analysis of 156 previously treated cases from the University of Arkansas for Medical Sciences. We correlated the presence of mutations with clinical outcome from diagnosis and compared the mutations found at diagnosis with later stages of disease.In diagnostic myeloma patient samples we identify significant mutations in genes encoding the histone 1 linker protein, previously identified in other B-cell malignancies. Our data suggest an adverse prognostic impact from the presence of lesions in genes encoding DNA methylation modifiers and the histone demethylase KDM6A/UTX. The frequency of mutations in epigenetic modifiers appears to increase following treatment most notably in genes encoding histone methyltransferases and DNA methylation modifiers.Numerous mutations identified raise the possibility of targeted treatment strategies for patients either at diagnosis or relapse supporting the use of sequencing-based diagnostics in myeloma to help guide therapy as more epigenetic targeted agents become available

Profiles of engagement in online communities of citizen science participation

Citizen participation in online communities of scientific investigations has recently become more popular. Enhancing the engagement of citizens within these communities is a focus of attention for researchers and practitioners who want to amplify the impact on learning, science and society. This study investigates the relationship between engagement factors and behaviour patterns in an online community that requires high levels of citizen participation. While other studies explore engagement in communities where citizens contribute data, the current research investigates a community to support citizens in facilitating their own scientific investigations. Data were collected from log files and questionnaires, and multiple measures of engagement were examined: engagement metrics, roles, motivation, attitude, satisfaction and belonging to the community. The results allowed comparison of the engagement levels among different types of citizen participation communities and categorised members in engagement profiles, according to their behaviour patterns. Findings indicate a need for differing design approaches based on the type of citizen participation community and individual engagement profiles

Genetic subtypes of smoldering multiple myeloma are associated with distinct pathogenic phenotypes and clinical outcomes

Smoldering multiple myeloma (SMM) is a precursor condition of multiple myeloma (MM) with significant heterogeneity in disease progression. Existing clinical models of progression risk do not fully capture this heterogeneity. Here we integrate 42 genetic alterations from 214 SMM patients using unsupervised binary matrix factorization (BMF) clustering and identify six distinct genetic subtypes. These subtypes are differentially associated with established MM-related RNA signatures, oncogenic and immune transcriptional profiles, and evolving clinical biomarkers. Three genetic subtypes are associated with increased risk of progression to active MM in both the primary and validation cohorts, indicating they can be used to better predict high and low-risk patients within the currently used clinical risk stratification models